The present invention relates generally to the field of detecting mechanical faults in HVAC equipment. More specifically, the present invention relates to a methodology for calculating vibration amplitude limits to detect mechanical faults in HVAC equipment such as chillers.
Timely detection, diagnosis and repair of mechanical problems in machinery such as heating, ventilating and air-conditioning (HVAC) systems is important for efficient operation. Chillers are important components of HVAC systems because they consume a large fraction of energy in a building and require a large capital investment. Severe mechanical faults in chillers typically results in expensive repairs and disruptions to the HVAC system during the repair period. Accordingly, chillers are generally monitored routinely to detect developing mechanical faults.
A common method for detecting and diagnosing mechanical faults is vibration analysis. By analyzing vibration data from different positions on a chiller, a vibration analyst can detect and diagnose mechanical faults in a machine. Vibration data is commonly available as a spectrum. The vibration analyst can determine a machine's condition by analyzing the vibration amplitude at different frequencies in the spectrum. A vibration analyst typically detects a mechanical fault that requires corrective action when the amplitudes in the vibration spectrum exceed “acceptable” limits. Under many current approaches, the acceptable limits are specified by rules-of-thumb or from a vibration analyst's experience. However, these approaches can be unreliable. For example, limits determined from an individual's experience can be incorrect or inconsistent. Similarly, limits specified by rules-of-thumb are typically generalized to apply to a large number of chillers and are therefore not likely relevant for some particular types of chillers.
Accordingly, there exists a need for a method of more accurately detecting mechanical faults without having to rely on an individual's knowledge of a system or general rule-of-thumb limits. In particular, it is desirable to be able to derive the limits from historical data using advanced statistical methods. By using statistics and historical data, the estimated limits may be based entirely on the vibration spectrum of each type of chiller. This approach easily allows updating of the amplitude limits when new vibration data from chillers is collected. In addition, because this approach uses statistical methods and not expert knowledge or “rules-of-thumb,” it results in more consistent limits. Many vendors also use rudimentary statistics such as calculating the average and standard deviation of the data to estimate limits. Unfortunately, this approach can result in erroneous limits because vibration data usually don't follow a bell shaped (or Gaussian) probability distribution.
It would be advantageous to provide a method or the like of a type disclosed in the present application that provides any one or more of these or other advantageous features. The present invention further relates to various features and combinations of features shown and described in the disclosed embodiments. Other ways in which the objects and features of the disclosed embodiments are accomplished will be described in the following specification or will become apparent to those skilled in the art after they have read this specification. Such other ways are deemed to fall within the scope of the disclosed embodiments if they fall within the scope of the claims which follow.